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首页> 外文期刊>Journal of Hydrology >Verification of precipitation in weather systems: determination of systematic errors
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Verification of precipitation in weather systems: determination of systematic errors

机译:验证天气系统中的降水:确定系统误差

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摘要

An object-oriented verification procedure is presented for gridded quantitative precipitation forecasts (QPFs). It is carried out within the framework of "contiguous rain areas" (CRAs), whereby a weather system is defined as a region bounded by a user-specified isopleth of precipitation in the union of the: forecast and observed rain fields. The horizontal displacement of the forecast is determined by translating the forecast rain field until the total squared difference between the observed and forecast fields is minimized. This allows a decomposition of total error into components due to: (a) location; (b) rain volume and (c) pattern. Results are first presented for a Monte Carlo simulation of 40,000 synthetic CRAs in order to determine the accuracy of the verification procedure when the rain systems are only partially observed due to the presence of domain boundaries. Verification is then carried out for operational 24-h forecasts from the Australian Bureau of Meteorology LAPS numerical weather prediction model over a four-year period. Forty-five percent of all rain events were well forecast by the model, with small location and intensity errors. Location error was generally the dominant source of QPF error, with the directions of most frequent displacement varying by region. Forty-five percent of extreme rainfall events (>100 mm d (1)) were well forecast, but in this case the model's underestimation of rain intensity was the most frequent sourer of error. (C) 2000 Elsevier Science B.V. All rights reserved. [References: 18]
机译:提出了面向对象的验证程序,用于网格化定量降水预报(QPF)。它是在“连续降雨区”(CRA)的框架内进行的,其中,天气系统的定义是一个由用户指定的降水等值线围成的区域,该降水量的等值线是:预测和观察到的雨场。预测的水平位移是通过平移预测的雨场来确定的,直到观测到的场与预测场之间的总平方差最小为止。由于以下原因,这可以将总误差分解为各个分量:(a)位置; (b)雨量和(c)模式。首先给出了40,000个合成CRA的蒙特卡罗模拟结果,以便确定当由于区域边界的存在而仅部分观测到雨水系统时验证程序的准确性。然后,在四年的时间内从澳大利亚气象局LAPS数值天气预报模型中对24小时运行预报进行验证。该模型对所有降雨事件的百分之四十五进行了很好的预测,位置和强度误差很小。位置误差通常是QPF误差的主要来源,最频繁位移的方向随区域而异。对极端降雨事件(> 100 mm d(1))的百分之四十五进行了很好的预测,但在这种情况下,该模型对降雨强度的低估是最常见的误差源。 (C)2000 Elsevier Science B.V.保留所有权利。 [参考:18]

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